Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = −0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.

Companies have repeatedly launched Artificial Intelligence (AI) products such as intelligent chatbots and robots with female names, voices, and bodies. Previous research posits that people intuitively favor female over male bots, mainly because female bots are judged as warmer and more likely to experience emotions. We present five online studies, including four preregistered, with a total sample of over 3,000 participants that go beyond this longstanding perception of femininity. Because warmth and experience (but not competence) are seen as fundamental qualities to be a full human but are lacking in machines, we argue that people prefer female bots because they are perceived as more human than male bots. Using implicit, subtle, and blatant scales of humanness, our results consistently show that women (Studies 1A and 1B), female bots (Studies 2 and 3), and female chatbots (Study 4) are perceived as more human than their male counterparts when compared with non‐human entities (animals and machines). Study 4 investigates explicitly the acceptance of gendered algorithms operated by AI chatbots in a health context. We found that the female chatbot is preferred over the male chatbot because it is perceived as more human and more likely to consider our unique needs. These results highlight the ethical quandary faced by AI designers and policymakers: Women are said to be transformed into objects in AI, but injecting women's humanity into AI objects makes these objects seem more human and acceptable.

Green consumption is associated with femininity. This green‐feminine stereotype has been accused of deterring men from buying green products to protect their gender identity. Here, we investigate whether men can benefit from this green‐feminine stereotype, beyond the status effect of green conspicuous consumption. We propose that green consumption can act as a signal of altruism and high commitment both as a partner and as a father. Based on evidence showing that these traits are sought in a long‐term partner, we predict that men can increase their value as long‐term mates by engaging in green consumption. We also investigate whether men involved in a long‐term mating relationship are indeed eco‐friendlier, testing the novel hypothesis that green consumption is an honest signal of commitment. Finally, we specify the type of commitment that is associated with men's green consumption. Across six studies, our findings suggest that green consumption is an honest signal of men's long‐term mating value and that it is a more reliable sign of partner commitment than of father commitment. We discuss how companies and governments can use these findings to increase green consumption among men.

The purpose of this article is to explain and illustrate the methodological approach used to test moderated mediation effects (conditional indirect effects) in marketing. A moderated mediation effect indicates the presence, in a single model, of one or more mediating variables and one or more moderating variables. Having first described the main methodological approaches used to test moderated mediation effects, with an emphasis on their respective advantages and disadvantages, we go on to recommend the method used by Hayes, which we illustrate through several marketing applications. This method makes it possible rigorously and simultaneously to test both mediating and moderating effects. Recommendations are also made to guide marketing researchers in the analysis of moderated mediation.

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